TY - GEN
T1 - A framework for collaborative cloud-based fault detection and diagnosis in smart buildings
AU - Lazarova-Molnar, Sanja
AU - Mohamed, Nader
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/5/26
Y1 - 2017/5/26
N2 - The potential for saving on energy related cost with timely and accurate Fault Detection and Diagnosis (FDD) in Building Management Systems (BMS) has been estimated to ca. 15-30% of the overall building energy-related cost. Due to the expansion of well-equipped smart buildings that feature multitudes of sensors and meters that enable collection of large amounts of data, FDD data-based methods have become very popular. Sensor and meter data, however, have been found as insufficient for FDD purposes, and it needs to be complemented with event/fault data that is more difficult to obtain. To account for the unavailability of event/fault data, BMS can benefit from sharing each other's data and utilize it for collaborative FDD. To support collaborative FDD and sharing of data, we rely on cloud computing. In this paper we present a framework for collaborative FDD of smart buildings that utilizes cloud computing and enables BMS to share and benefit from each other's data.
AB - The potential for saving on energy related cost with timely and accurate Fault Detection and Diagnosis (FDD) in Building Management Systems (BMS) has been estimated to ca. 15-30% of the overall building energy-related cost. Due to the expansion of well-equipped smart buildings that feature multitudes of sensors and meters that enable collection of large amounts of data, FDD data-based methods have become very popular. Sensor and meter data, however, have been found as insufficient for FDD purposes, and it needs to be complemented with event/fault data that is more difficult to obtain. To account for the unavailability of event/fault data, BMS can benefit from sharing each other's data and utilize it for collaborative FDD. To support collaborative FDD and sharing of data, we rely on cloud computing. In this paper we present a framework for collaborative FDD of smart buildings that utilizes cloud computing and enables BMS to share and benefit from each other's data.
KW - Cloud computing
KW - Collaborative processing
KW - Fault detection and diagnosis
KW - Smart buildings
UR - http://www.scopus.com/inward/record.url?scp=85021440252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021440252&partnerID=8YFLogxK
U2 - 10.1109/ICMSAO.2017.7934905
DO - 10.1109/ICMSAO.2017.7934905
M3 - Conference contribution
AN - SCOPUS:85021440252
T3 - 2017 7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017
BT - 2017 7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017
Y2 - 4 April 2017 through 6 April 2017
ER -